central tendency eigen reeks

*Unverified author*

R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Wed, 27 Jan 2010 08:05:08 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/27/t1264604799dqmwz7wd1zvyidl.htm/, Retrieved Wed, 27 Jan 2010 16:06:41 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Jan/27/t1264604799dqmwz7wd1zvyidl.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDG91WK52

Dataseries X:

» Textbox « » Textfile « » CSV «

176.9 177.3 177.3 177.5 177.6 177.3 177.8 179.6 179.7 179.8 179.1 179.1 179.3 179.3 179.6 179.8 180.2 180.1 179.9 179.9 179.2 179.7 179.9 180.2 181.1 181.3 181.3 181.4 181.3 181.4 181.5 181.7 181.9 182.0 182.1 182.1 187.2 188.1 188.0 188.2 188.6 188.5 188.6 188.5 189.2 189.3 189.4 189.4 189.4 189.6 189.7 189.7 189.8 190.1 190.0 190.0 190.2 190.3 190.3 190.2 190.6 190.5 190.8 190.8 190.8 191.0 191.3 191.3 191.2 191.2 191.4 191.5 194.1 193.9 193.9 193.7 194.8 194.8 194.8 195.3 195.4 196.1 196.1 196.0 197.8 198.5 198.9 198.5 199.2 199.2 199.3 199.3 200.5 201.4 201.6 201.4 204.9 206.2 207.4 209.0 210.1 210.3 213.8 213.8 213.6 216.5 216.4 216.6 220.9 220.3 220.3 220.4 221.2 221.1 221.8 221.7

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean 192.678448275862 1.15688137757975 166.549874524693 Geometric Mean 192.292404572350 Harmonic Mean 191.919465667094 Quadratic Mean 193.077439127413 Winsorized Mean ( 1 / 38 ) 192.681034482759 1.15628905058614 166.637428924096 Winsorized Mean ( 2 / 38 ) 192.672413793103 1.15442216456690 166.899440869093 Winsorized Mean ( 3 / 38 ) 192.669827586207 1.15386724753280 166.977464693771 Winsorized Mean ( 4 / 38 ) 192.669827586207 1.15159899254105 167.306353022307 Winsorized Mean ( 5 / 38 ) 192.652586206897 1.14654128288242 168.029349734852 Winsorized Mean ( 6 / 38 ) 192.657758620690 1.144279266077 168.366031205992 Winsorized Mean ( 7 / 38 ) 192.736206896552 1.13575421021213 169.698870727103 Winsorized Mean ( 8 / 38 ) 192.481034482759 1.08409374182730 177.550175834721 Winsorized Mean ( 9 / 38 ) 192.481034482759 1.08176372850429 177.932601556991 Winsorized Mean ( 10 / 38 ) 192.481034482759 1.07918281718771 178.358134893543 Winsorized Mean ( 11 / 38 ) 192.234482758621 1.03301505077363 186.090689205985 Winsorized Mean ( 12 / 38 ) 192.265517241379 1.02966574644285 186.726146718575 Winsorized Mean ( 13 / 38 ) 192.243103448276 1.02559831817909 187.444831022731 Winsorized Mean ( 14 / 38 ) 191.856896551724 0.954678548330053 200.964918387791 Winsorized Mean ( 15 / 38 ) 191.831034482759 0.950344697027385 201.854164160429 Winsorized Mean ( 16 / 38 ) 191.693103448276 0.923762370822725 207.513435817427 Winsorized Mean ( 17 / 38 ) 191.458620689655 0.886309388014498 216.017818697102 Winsorized Mean ( 18 / 38 ) 191.287931034483 0.85584869822971 223.506714948745 Winsorized Mean ( 19 / 38 ) 191.075 0.824177273655853 231.837258933915 Winsorized Mean ( 20 / 38 ) 190.506034482759 0.745641296280119 255.492869605213 Winsorized Mean ( 21 / 38 ) 190.506034482759 0.736507102364763 258.661503563354 Winsorized Mean ( 22 / 38 ) 190.525 0.734182402812612 259.506356009228 Winsorized Mean ( 23 / 38 ) 190.346551724138 0.711613272660657 267.485949232579 Winsorized Mean ( 24 / 38 ) 190.284482758621 0.658565525135477 288.937813317022 Winsorized Mean ( 25 / 38 ) 190.327586206897 0.65336240945688 291.304769683812 Winsorized Mean ( 26 / 38 ) 190.305172413793 0.650691991043208 292.465828738249 Winsorized Mean ( 27 / 38 ) 190.305172413793 0.650691991043208 292.465828738249 Winsorized Mean ( 28 / 38 ) 190.256896551724 0.639224164468675 297.637209491081 Winsorized Mean ( 29 / 38 ) 190.156896551724 0.627564273798328 303.007842369358 Winsorized Mean ( 30 / 38 ) 190.182758620690 0.624431706686124 304.569349352861 Winsorized Mean ( 31 / 38 ) 190.049137931034 0.596541124213616 318.585140599594 Winsorized Mean ( 32 / 38 ) 189.635344827586 0.538678284617412 352.038220664996 Winsorized Mean ( 33 / 38 ) 189.663793103448 0.535130743250096 354.425148425472 Winsorized Mean ( 34 / 38 ) 189.663793103448 0.528420742010846 358.925715863658 Winsorized Mean ( 35 / 38 ) 189.482758620690 0.509842077825030 371.649902709124 Winsorized Mean ( 36 / 38 ) 191.034482758621 0.320634919802126 595.800616091703 Winsorized Mean ( 37 / 38 ) 191.130172413793 0.276311700193003 691.719432366742 Winsorized Mean ( 38 / 38 ) 191.162931034483 0.273100719986221 699.97227046537 Trimmed Mean ( 1 / 38 ) 192.561403508772 1.14047257898584 168.843518955981 Trimmed Mean ( 2 / 38 ) 192.4375 1.12275954869364 171.396894574538 Trimmed Mean ( 3 / 38 ) 192.313636363636 1.10399719366683 174.197577192097 Trimmed Mean ( 4 / 38 ) 192.186111111111 1.08315196048084 177.432270007428 Trimmed Mean ( 5 / 38 ) 192.053773584906 1.06042437937907 181.110296330005 Trimmed Mean ( 6 / 38 ) 191.920192307692 1.03619195308781 185.216833363526 Trimmed Mean ( 7 / 38 ) 191.780392156863 1.00930541287286 190.012249722296 Trimmed Mean ( 8 / 38 ) 191.622 0.980514789549476 195.429994572592 Trimmed Mean ( 9 / 38 ) 191.494897959184 0.958625862351982 199.759786878013 Trimmed Mean ( 10 / 38 ) 191.3625 0.934098507615672 204.863297007573 Trimmed Mean ( 11 / 38 ) 191.224468085106 0.906482521012889 210.952184573217 Trimmed Mean ( 12 / 38 ) 191.108695652174 0.88318643580863 216.385451478541 Trimmed Mean ( 13 / 38 ) 190.984444444444 0.856901061087079 222.87805805977 Trimmed Mean ( 14 / 38 ) 190.856818181818 0.827230204046805 230.717903248875 Trimmed Mean ( 15 / 38 ) 190.760465116279 0.804889774288687 237.001973698649 Trimmed Mean ( 16 / 38 ) 190.661904761905 0.779708789736664 244.529633719146 Trimmed Mean ( 17 / 38 ) 190.570731707317 0.754755051396668 252.493482958037 Trimmed Mean ( 18 / 38 ) 190.495 0.731735192815723 260.333248790418 Trimmed Mean ( 19 / 38 ) 190.429487179487 0.709659599034186 268.339197325947 Trimmed Mean ( 20 / 38 ) 190.377631578947 0.688788916012585 276.394737419771 Trimmed Mean ( 21 / 38 ) 190.367567567568 0.675991484877735 281.612375046409 Trimmed Mean ( 22 / 38 ) 190.356944444444 0.66215854397472 287.479405312502 Trimmed Mean ( 23 / 38 ) 190.344285714286 0.646098774295472 294.60555148374 Trimmed Mean ( 24 / 38 ) 190.344117647059 0.630336331592899 301.972309236955 Trimmed Mean ( 25 / 38 ) 190.348484848485 0.61914762983121 307.436345836254 Trimmed Mean ( 26 / 38 ) 190.35 0.606377318491509 313.913456515055 Trimmed Mean ( 27 / 38 ) 190.353225806452 0.591298250510942 321.924216149747 Trimmed Mean ( 28 / 38 ) 190.356666666667 0.572951357449973 332.238791638237 Trimmed Mean ( 29 / 38 ) 190.363793103448 0.552416997271028 344.601621680463 Trimmed Mean ( 30 / 38 ) 190.378571428571 0.529123965329918 359.799562867781 Trimmed Mean ( 31 / 38 ) 190.378571428571 0.500704268868058 380.221586404606 Trimmed Mean ( 32 / 38 ) 190.417307692308 0.470492194015275 404.71937710007 Trimmed Mean ( 33 / 38 ) 190.474 0.443573705998295 429.407779190438 Trimmed Mean ( 34 / 38 ) 190.533333333333 0.409563568673863 465.210648374479 Trimmed Mean ( 35 / 38 ) 190.597826086957 0.36596096951988 520.814627682865 Trimmed Mean ( 36 / 38 ) 190.681818181818 0.309850143265988 615.400129146074 Trimmed Mean ( 37 / 38 ) 190.654761904762 0.293328893053562 649.969254375321 Trimmed Mean ( 38 / 38 ) 190.6175 0.281795695677852 676.438650141462 Median 190.25 Midrange 199.35 Midmean - Weighted Average at Xnp 190.211864406780 Midmean - Weighted Average at X(n+1)p 190.211864406780 Midmean - Empirical Distribution Function 190.211864406780 Midmean - Empirical Distribution Function - Averaging 190.211864406780 Midmean - Empirical Distribution Function - Interpolation 190.211864406780 Midmean - Closest Observation 190.211864406780 Midmean - True Basic - Statistics Graphics Toolkit 190.211864406780 Midmean - MS Excel (old versions) 190.356666666667 Number of observations 116

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/27/t1264604799dqmwz7wd1zvyidl/1hsc51264604704.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/27/t1264604799dqmwz7wd1zvyidl/1hsc51264604704.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/27/t1264604799dqmwz7wd1zvyidl/2ou7r1264604704.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/27/t1264604799dqmwz7wd1zvyidl/2ou7r1264604704.ps (open in new window)

Parameters (Session):

Parameters (R input):

R code (references can be found in the software module):

geomean <- function(x) { return(exp(mean(log(x)))) } harmean <- function(x) { return(1/mean(1/x)) } quamean <- function(x) { return(sqrt(mean(x*x))) } winmean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) win <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn } return(win) } trimean <- function(x) { x <-sort(x[!is.na(x)]) n<-length(x) denom <- 3 nodenom <- n/denom if (nodenom>40) denom <- n/40 sqrtn = sqrt(n) roundnodenom = floor(nodenom) tri <- array(NA,dim=c(roundnodenom,2)) for (j in 1:roundnodenom) { tri[j,1] <- mean(x,trim=j/n) tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2) } return(tri) } midrange <- function(x) { return((max(x)+min(x))/2) } q1 <- function(data,n,p,i,f) { np <- n*p; i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q2 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i qvalue <- (1-f)*data[i] + f*data[i+1] } q3 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- data[i+1] } } q4 <- function(data,n,p,i,f) { np <- n*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- (data[i]+data[i+1])/2 } else { qvalue <- data[i+1] } } q5 <- function(data,n,p,i,f) { np <- (n-1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i+1] } else { qvalue <- data[i+1] + f*(data[i+2]-data[i+1]) } } q6 <- function(data,n,p,i,f) { np <- n*p+0.5 i <<- floor(np) f <<- np - i qvalue <- data[i] } q7 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { qvalue <- f*data[i] + (1-f)*data[i+1] } } q8 <- function(data,n,p,i,f) { np <- (n+1)*p i <<- floor(np) f <<- np - i if (f==0) { qvalue <- data[i] } else { if (f == 0.5) { qvalue <- (data[i]+data[i+1])/2 } else { if (f < 0.5) { qvalue <- data[i] } else { qvalue <- data[i+1] } } } } midmean <- function(x,def) { x <-sort(x[!is.na(x)]) n<-length(x) if (def==1) { qvalue1 <- q1(x,n,0.25,i,f) qvalue3 <- q1(x,n,0.75,i,f) } if (def==2) { qvalue1 <- q2(x,n,0.25,i,f) qvalue3 <- q2(x,n,0.75,i,f) } if (def==3) { qvalue1 <- q3(x,n,0.25,i,f) qvalue3 <- q3(x,n,0.75,i,f) } if (def==4) { qvalue1 <- q4(x,n,0.25,i,f) qvalue3 <- q4(x,n,0.75,i,f) } if (def==5) { qvalue1 <- q5(x,n,0.25,i,f) qvalue3 <- q5(x,n,0.75,i,f) } if (def==6) { qvalue1 <- q6(x,n,0.25,i,f) qvalue3 <- q6(x,n,0.75,i,f) } if (def==7) { qvalue1 <- q7(x,n,0.25,i,f) qvalue3 <- q7(x,n,0.75,i,f) } if (def==8) { qvalue1 <- q8(x,n,0.25,i,f) qvalue3 <- q8(x,n,0.75,i,f) } midm <- 0 myn <- 0 roundno4 <- round(n/4) round3no4 <- round(3*n/4) for (i in 1:n) { if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){ midm = midm + x[i] myn = myn + 1 } } midm = midm / myn return(midm) } (arm <- mean(x)) sqrtn <- sqrt(length(x)) (armse <- sd(x) / sqrtn) (armose <- arm / armse) (geo <- geomean(x)) (har <- harmean(x)) (qua <- quamean(x)) (win <- winmean(x)) (tri <- trimean(x)) (midr <- midrange(x)) midm <- array(NA,dim=8) for (j in 1:8) midm[j] <- midmean(x,j) midm bitmap(file='test1.png') lb <- win[,1] - 2*win[,2] ub <- win[,1] + 2*win[,2] if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() bitmap(file='test2.png') lb <- tri[,1] - 2*tri[,2] ub <- tri[,1] + 2*tri[,2] if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax)) lines(ub,lty=3) lines(lb,lty=3) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Measure',header=TRUE) a<-table.element(a,'Value',header=TRUE) a<-table.element(a,'S.E.',header=TRUE) a<-table.element(a,'Value/S.E.',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE) a<-table.element(a,arm) a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean')) a<-table.element(a,armose) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE) a<-table.element(a,geo) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE) a<-table.element(a,har) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE) a<-table.element(a,qua) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) for (j in 1:length(win[,1])) { a<-table.row.start(a) mylabel <- paste('Winsorized Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(win[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE) a<-table.element(a,win[j,1]) a<-table.element(a,win[j,2]) a<-table.element(a,win[j,1]/win[j,2]) a<-table.row.end(a) } for (j in 1:length(tri[,1])) { a<-table.row.start(a) mylabel <- paste('Trimmed Mean (',j) mylabel <- paste(mylabel,'/') mylabel <- paste(mylabel,length(tri[,1])) mylabel <- paste(mylabel,')') a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE) a<-table.element(a,tri[j,1]) a<-table.element(a,tri[j,2]) a<-table.element(a,tri[j,1]/tri[j,2]) a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE) a<-table.element(a,median(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE) a<-table.element(a,midr) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[1]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[2]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[3]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[4]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[5]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[6]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[7]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean') mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ') a<-table.element(a,mylabel,header=TRUE) a<-table.element(a,midm[8]) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Number of observations',header=TRUE) a<-table.element(a,length(x)) a<-table.element(a,'') a<-table.element(a,'') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

• personalize online software applications according to your needs
• enforce strict security rules with respect to the data that you upload (e.g. statistical data)
• manage user sessions of online applications
• alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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